This K01 application seeks funding for an intensive 5-year research, training and career development program. The PI is currently a RWJ Fellow, and she plans an independent research career in social determinants of population health and healthy aging. This K01 program is individually tailored to foster increasing independence in a highly productive and scientifically and intellectually enriched environment. Under the direction of an exceptional mentoring and advisory committee, the PI aims to solidify specialized training, conduct focused research, and emerge from this program as an independent researcher with (I) an established record of research by publishing an significant number of manuscripts and (II) a fully funded program of research as PI and as collaborator of related projects. The research component of this program aims to investigate the dynamics of the complex clustering of exposures and diseases/functional outcomes over time and to examine the contribution of risk factors-morbidities clusters on subsequent functional decline and mortality. The project is based on data from SPPARCS (The Study of Physical Performance and Age-Related Changes in Sonomans), a National Institute on Aging-funded longitudinal study on physical functioning and physical activity, morbidity and mortality in the elderly. Computational methods for complex data analysis will be applied to address the following specific aims: (1) to identify clusters of risk factors, morbidities, and functional outcomes, and describe the dynamics of these clusters over time;(2) to estimate the relationship among clusters of risk factors, morbidities and functional outcomes, with respect to one another over time as well as with respect to mortality;and (3) to describe transitions to disablement and mortality with respect to changes over time in the clustering of risk factors, morbidities and functional outcomes. The strategy of this project focuses on assessing the value added from computational methods, such as Grade of Membership (GoM) and Random Forests (RF), in comparison with existing state-of-the-art statistical methods for longitudinal data analysis and cluster analysis. The overall goal of this strategy is to facilitate the development of simplified ways in which computational methods may be incorporated in applied population health and aging research settings and particularly, in the translation of research findings into programs and policies aimed at the promotion of healthy aging in the population.